IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v222y2014i1p517-53310.1007-s10479-014-1538-1.html
   My bibliography  Save this article

Solution algorithms for unrelated machines minmax regret scheduling problem with interval processing times and the total flow time criterion

Author

Listed:
  • Marcin Siepak
  • Jerzy Józefczyk

Abstract

An uncertain version of the task scheduling problem on unrelated machines to minimize the total flow time is considered. It is assumed that processing times are not known a priori, but they belong to intervals of known bounds. The absolute regret is applied to evaluate the uncertainty, and minmax regret task scheduling problem is solved. A simple 2-approximate middle intervals time efficient algorithm is proposed. More time consuming but better in terms of the quality of solutions scatter search based heuristic algorithm is described. Its usefulness is justified via computational experiments. Copyright The Author(s) 2014

Suggested Citation

  • Marcin Siepak & Jerzy Józefczyk, 2014. "Solution algorithms for unrelated machines minmax regret scheduling problem with interval processing times and the total flow time criterion," Annals of Operations Research, Springer, vol. 222(1), pages 517-533, November.
  • Handle: RePEc:spr:annopr:v:222:y:2014:i:1:p:517-533:10.1007/s10479-014-1538-1
    DOI: 10.1007/s10479-014-1538-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-014-1538-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-014-1538-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 2006. "Some aspects of scatter search in the flow-shop problem," European Journal of Operational Research, Elsevier, vol. 169(2), pages 654-666, March.
    2. W. A. Horn, 1973. "Technical Note—Minimizing Average Flow Time with Parallel Machines," Operations Research, INFORMS, vol. 21(3), pages 846-847, June.
    3. A Corberán & E Fernández & M Laguna & R Martí, 2002. "Heuristic solutions to the problem of routing school buses with multiple objectives," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 427-435, April.
    4. Kasperski, Adam & Zielinski, Pawel, 2010. "Minmax regret approach and optimality evaluation in combinatorial optimization problems with interval and fuzzy weights," European Journal of Operational Research, Elsevier, vol. 200(3), pages 680-687, February.
    5. Aissi, Hassene & Bazgan, Cristina & Vanderpooten, Daniel, 2009. "Min-max and min-max regret versions of combinatorial optimization problems: A survey," European Journal of Operational Research, Elsevier, vol. 197(2), pages 427-438, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michał Ćwik & Jerzy Józefczyk, 2018. "Heuristic algorithms for the minmax regret flow-shop problem with interval processing times," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(1), pages 215-238, March.
    2. Zhi Pei & Mingzhong Wan & Ziteng Wang, 2020. "A new approximation algorithm for unrelated parallel machine scheduling with release dates," Annals of Operations Research, Springer, vol. 285(1), pages 397-425, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chassein, André & Goerigk, Marc, 2018. "Compromise solutions for robust combinatorial optimization with variable-sized uncertainty," European Journal of Operational Research, Elsevier, vol. 269(2), pages 544-555.
    2. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    3. Ravindran Vijayalakshmi, Vipin & Schröder, Marc & Tamir, Tami, 2024. "Minimizing total completion time with machine-dependent priority lists," European Journal of Operational Research, Elsevier, vol. 315(3), pages 844-854.
    4. Hernan Caceres & Rajan Batta & Qing He, 2017. "School Bus Routing with Stochastic Demand and Duration Constraints," Transportation Science, INFORMS, vol. 51(4), pages 1349-1364, November.
    5. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    6. Alireza Amirteimoori & Simin Masrouri, 2021. "DEA-based competition strategy in the presence of undesirable products: An application to paper mills," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 5-21.
    7. Adam Kasperski & Paweł Zieliński, 2019. "Risk-averse single machine scheduling: complexity and approximation," Journal of Scheduling, Springer, vol. 22(5), pages 567-580, October.
    8. Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
    9. Haokai Xie & Pu Zhao & Xudong Ji & Qun Lin & Lianguang Liu, 2019. "Expansion Planning Method of the Industrial Park Integrated Energy System Considering Regret Aversion," Energies, MDPI, vol. 12(21), pages 1-20, October.
    10. Jiang, Xiaojuan & Lee, Kangbok & Pinedo, Michael L., 2021. "Ideal schedules in parallel machine settings," European Journal of Operational Research, Elsevier, vol. 290(2), pages 422-434.
    11. Chassein, André & Goerigk, Marc, 2018. "Variable-sized uncertainty and inverse problems in robust optimization," European Journal of Operational Research, Elsevier, vol. 264(1), pages 17-28.
    12. Detienne, Boris & Lefebvre, Henri & Malaguti, Enrico & Monaci, Michele, 2024. "Adjustable robust optimization with objective uncertainty," European Journal of Operational Research, Elsevier, vol. 312(1), pages 373-384.
    13. Chen, Chialin & Achtari, Guyves & Majkut, Kevin & Sheu, Jiuh-Biing, 2017. "Balancing equity and cost in rural transportation management with multi-objective utility analysis and data envelopment analysis: A case of Quinte West," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 148-165.
    14. Ohad Eisenhandler & Michal Tzur, 2019. "The Humanitarian Pickup and Distribution Problem," Operations Research, INFORMS, vol. 67(1), pages 10-32, January.
    15. Lenstra, J. K. & Rinnooy Kan, A. H. G., 1980. "An Introduction To Multiprocessor Scheduling," Econometric Institute Archives 272258, Erasmus University Rotterdam.
    16. Machani, Mahdi & Nourelfath, Mustapha & D’Amours, Sophie, 2015. "A scenario-based modelling approach to identify robust transformation strategies for pulp and paper companies," International Journal of Production Economics, Elsevier, vol. 168(C), pages 41-63.
    17. Schroeder, Pascal & Kacem, Imed, 2020. "Competitive difference analysis of the cash management problem with uncertain demands," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1183-1192.
    18. Vikneswari Someetheram & Muhammad Fadhil Marsani & Mohd Shareduwan Mohd Kasihmuddin & Nur Ezlin Zamri & Siti Syatirah Muhammad Sidik & Siti Zulaikha Mohd Jamaludin & Mohd. Asyraf Mansor, 2022. "Random Maximum 2 Satisfiability Logic in Discrete Hopfield Neural Network Incorporating Improved Election Algorithm," Mathematics, MDPI, vol. 10(24), pages 1-29, December.
    19. Russell, Robert A. & Chiang, Wen-Chyuan, 2006. "Scatter search for the vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 169(2), pages 606-622, March.
    20. Jose Gonzalez-Velarde & Salvador Garcia-Lumbreras & Alberto Garcia-Diaz, 2008. "A multi-stop routing problem," Annals of Operations Research, Springer, vol. 157(1), pages 153-167, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:222:y:2014:i:1:p:517-533:10.1007/s10479-014-1538-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.